A novel framework based on FastICA for high density surface EMG decomposition

IEEE Transactions on Neural Systems and Rehabilitation Engineering

Volumn 24, Issue 1, 2016, Pages 117-127

  Chen, Maoqi ^a   Zhou, Ping ^a,b  

^a UNIVERSITY OF SCIENCE AND TECHNOLOGY OF CHINA   (China)

^b UNIVERSITY OF TEXAS MEDICAL SCHOOL   (United States)

Author keywords

Constrained FastICA; Decomposition; FastICA; High density surface EMG; Motor unit spike train; MUAP waveform estimation.

Indexed keywords

DECOMPOSITION; ELECTROMYOGRAPHY;

DECOMPOSITION PERFORMANCE; DECOMPOSITION PROCESS; FAST-ICA; HIGH-DENSITY SURFACE EMG; MOTOR UNIT ACTION POTENTIALS; MUSCLE CONTRACTIONS; SPIKE TRAIN; WAVE FORMS;

MUSCLE;

ACTION POTENTIAL; ALGORITHM; ARTICLE; CONCEPTUAL FRAMEWORK; DECOMPOSITION; ELECTROMYOGRAM; ELECTROMYOGRAPHY; FASTICA; HIGH DENSITY SURFACE ELECTROMYOGRAM; MATHEMATICAL MODEL; MOTOR UNIT; MUSCLE CONTRACTION; SIGNAL NOISE RATIO; SIGNAL PROCESSING; SIMULATION; AUTOMATED PATTERN RECOGNITION; COMPUTER SIMULATION; HUMAN; MUSCLE ISOMETRIC CONTRACTION; PHYSIOLOGY; PRINCIPAL COMPONENT ANALYSIS; PROCEDURES; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY; SKELETAL MUSCLE; STATISTICAL ANALYSIS; STATISTICAL MODEL;

ACTION POTENTIALS; ALGORITHMS; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; ELECTROMYOGRAPHY; HUMANS; ISOMETRIC CONTRACTION; MODELS, STATISTICAL; MUSCLE, SKELETAL; PATTERN RECOGNITION, AUTOMATED; PRINCIPAL COMPONENT ANALYSIS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY;

EID: 85014725528     PISSN: 15344320     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNSRE.2015.2412038     Document Type: Article

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